Package: EBMAforecast 1.0.33

EBMAforecast: Estimate Ensemble Bayesian Model Averaging Forecasts using Gibbs Sampling or EM-Algorithms

Create forecasts from multiple predictions using ensemble Bayesian model averaging (EBMA). EBMA models can be estimated using an expectation maximization (EM) algorithm or as fully Bayesian models via Gibbs sampling. The methods in this package are Montgomery, Hollenbach, and Ward (2015) <doi:10.1016/j.ijforecast.2014.08.001> and Montgomery, Hollenbach, and Ward (2012) <doi:10.1093/pan/mps002>.

Authors:Florian M. Hollenbach [aut, cre], Jacob M. Montgomery [aut], Michael D. Ward [aut]

EBMAforecast_1.0.33.tar.gz
EBMAforecast_1.0.33.zip(r-4.7-x86_64)EBMAforecast_1.0.33.zip(r-4.7-arm64)EBMAforecast_1.0.33.zip(r-4.6-x86_64)EBMAforecast_1.0.33.zip(r-4.6-arm64)EBMAforecast_1.0.33.zip(r-4.5-x86_64)
EBMAforecast_1.0.33.tgz(r-4.6-x86_64)EBMAforecast_1.0.33.tgz(r-4.6-arm64)EBMAforecast_1.0.33.tgz(r-4.5-x86_64)EBMAforecast_1.0.33.tgz(r-4.5-arm64)
EBMAforecast_1.0.33.tar.gz(r-4.7-arm64)EBMAforecast_1.0.33.tar.gz(r-4.7-x86_64)EBMAforecast_1.0.33.tar.gz(r-4.6-arm64)EBMAforecast_1.0.33.tar.gz(r-4.6-x86_64)
EBMAforecast_1.0.33.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
EBMAforecast/json (API)

# Install 'EBMAforecast' in R:
install.packages('EBMAforecast', repos = c('https://fhollenbach.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/fhollenbach/ebma/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

3.04 score 2 stars 11 scripts 481 downloads 13 exports 61 dependencies

Last updated from:a3d7f651a6. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK159
linux-devel-x86_64OK142
source / vignettesOK210
linux-release-arm64OK113
linux-release-x86_64OK142
macos-release-arm64OK199
macos-release-x86_64OK323
macos-oldrel-arm64OK209
macos-oldrel-x86_64OK268
windows-devel-arm64OK355
windows-devel-x86_64OK165
windows-release-arm64OK358
windows-release-x86_64OK105
windows-oldrel-x86_64OK106
wasm-releaseOK105

Exports:calibrateEnsemblecompareModelsEBMApredictmakeForecastDataplotprintsetModelNames<-setOutcomeCalibration<-setOutcomeTest<-setPredCalibration<-setPredTest<-showsummary

Dependencies:abindbackportsbase64encbslibcachemcheckmatecliclustercolorspacecpp11data.tabledigestevaluatefarverfastmapfontawesomeforeignFormulafsggplot2gluegridExtragtablegtoolshighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglifecyclemagrittrMASSmemoisemimennetplyrR6rappdirsRColorBrewerRcpprlangrmarkdownrpartrstudioapiS7sassscalesseparationplotstringistringrtinytexvctrsviridisLitewithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
Calibrate an ensemble Bayesian Model Averaging modelcalibrateEnsemble calibrateEnsemble,ForecastData-method
Sample data Insurgency PredictionscalibrationSample testSample
Function for comparing multiple models based on predictive performancecompareModels compareModels,ForecastData-method CompareModels-class
EBMApredictEBMApredict EBMApredict,ForecastData-method
An ensemble forecasting data objectForecastData-class
Build a ensemble forecasting data objectmakeForecastData makeForecastData,ANY-method
Sample data Presidential ElectionpresidentialForecast
Print and Show methods for forecast dataprint,ForecastData-method print,SummaryForecastData-method show,ForecastData-method show,SummaryForecastData-method
"Set" functionssetModelNames<- setModelNames<-,ForecastData-method setOutcomeCalibration<- setOutcomeCalibration<-,ForecastData-method setOutcomeTest<- setOutcomeTest<-,ForecastData-method setPredCalibration<- setPredCalibration<-,ForecastData-method setPredTest<- setPredTest<-,ForecastData-method
Summarize and Plot Ensemble modelsplot,FDatFitLogit-method plot,FDatFitNormal-method summary,FDatFitLogit-method summary,FDatFitNormal-method SummaryForecastData-class